neuro fuzzy based multilevel inverter thesis report ....etc

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Im Dora..I need ppt on Neuro fuzzy logic for Embedded system applications Or ppt on Neuro-Fuzzy Real-time controller for low power Embedded systems. ....etc

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ADAPTIVE-NETWORK-BASED FUZZY INFERENCE SYSTEMS


Set Operations

• Containment or Subset,
• Union (disjunction),
• Intersection (conjunction),
• Complement (negation),
• Probabilistic AND,
• Probabilistic OR.

Partition styles for fuzzy models

• Grid partition - often chosen in designing a fuzzy controller,
problems when we have moderately large number of inputs.
• Tree partition - relives the problem of an exponential increase
in the number of rules.
• Scatter partition. ....etc

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defination of neuro-fuzzy system,models,areas of application ....etc

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In this context, FL (Fuzzy Logic) is a problem-solving control system methodology that lends itself to implementation in systems ranging from simple, small, embedded micro-controllers to large, networked, multi-channel PC or workstation-based data acquisition and control systems. It can be implemented in hardware, software, or a combination of both. FL provides a simple way to arrive at a definite conclusion based upon vague, ambiguous, imprecise, noisy, or missing input information. FL's approach to control problems mimics how a person would m ....etc

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i want to know about it . i am a student. ....etc

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Torque Ripple Minimization in a Switched
Reluctance Drive by Neuro-fuzzy
Compensation

Simple power electronic drive circuit and fault tolerance of converter are specific advantages of SRM drives, but excessive torque ripple has limited its use to special applications. A new method for shaping the motor currents so that the ripple can be reduced is presented by this paper. Here, a compensating signal is added to the output of a PI
controller. This i ....etc

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Adaptive Network Based Fuzzy Inference Systems (ANFIS)



ANFIS is an adaptive network. An adaptive network is network of nodes and directional links. Associated with the network is a learning rule - for example back propagation. It’s called adaptive because some, or all, of the nodes have parameters which affect the output of the node. These networks are learning a relationship between inputs and outputs.
Adaptive networks covers a number of different approaches but for our purposes we will investigate in som ....etc

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Adaptive Neuro-Fuzzy Inference System usingParticle Swarm Optimization and it’s Application


INTRODUCTION

The Adaptive Neuro-Fuzzy Inference System combines the concept of Fuzzy logic and Neural network to form a hybrid intelligent system that enhances the ability to automatically learn and adapt.

The Particle Swarm Optimization algorithm used to get the optimal values and parameters of our ANFIS model.


NEURAL NETWORK

A Neura ....etc

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NEW TRENDS IN HVDC TRANSMISSION BASED ON ADAPTIVE NEURO-FUZZY INTERFACE SYSTEM (ANFIS)
ABSTRACT
The industrial growth of a world requires increased consumption of energy, particularly electrical energy. This has led to increase in the generation and transmission facilities to meet the increasing demand. In developing countries like India, the demand doubles every seven years which requires considerable investment in electric power sector. The problems of AC transmission particularly in long distance transmis ....etc

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